A Dual-Modal, Label-Free Raman Imaging Method for Rapid Virtual Staining of Large-Area Breast Cancer Tissue Sections.

As one of the most common cancers, accurate, rapid, and simple histopathological diagnosis is very important for breast cancer. Raman imaging is a powerful technique for label-free analysis of tissue composition and histopathology, but it suffers from slow speed when applied to large-area tissue sections. In this study, we propose a dual-modal Raman imaging method that combines Raman mapping data with microscopy bright-field images to achieve virtual staining of breast cancer tissue sections. We validate our method on various breast tissue sections with different morphologies and biomarker expressions and compare it with the golden standard of histopathological methods. The results demonstrate that our method can effectively distinguish various types and components of tissues, and provide staining images comparable to stained tissue sections. Moreover, our method can improve imaging speed by up to 65 times compared to general spontaneous Raman imaging methods. It is simple, fast, and suitable for clinical applications.

Picosecond laser-driven coded-source radiography with high resolution and contrast.

The X-ray sources for Compton radiography of ICF experiments are generated by using intense picosecond lasers to irradiate wire targets. The wire diameter must be designed thin enough, for example ∼ 10 µm in many published works, to comply a high spatial resolution. This results in a low laser-target interception, which limits the photon yield. We investigated a technique of coded-source radiography based on laser-driven annular sources via Monte Carlo and PIC simulations. The annular X-ray source is formed by laser irradiating tube target in which the effect of electron recirculation plays an important role. We proved that this technique has an increased spatial resolution and contrast than that using the Gaussian source produced by wire targets. Therefore, the diameter of the backlighter target can be significantly increased to uplift laser-target interception without compromising on spatial resolution. This contributes towards a reconciliation between the spatial resolution and photon yield for Compton radiography. The results predict the possibility of improving source photon yield by several times in future experiments.

Association of maternal body mass index and gestational weight gain rate with cardiometabolic traits in childhood: A prospective cohort study.

BACKGROUND AND AIMS: Evidence on the association of maternal obesity with offspring cardiometabolic health is limited, particularly for the Asian population. We aimed to examine the associations of maternal body mass index (BMI) in early pregnancy and gestational weight gain (GWG) rate in mid- and late-pregnancy with childhood cardiometabolic traits. METHODS AND RESULTS: We used data of 1452 mother-child pairs from a population-based prospective cohort study in China. Maternal BMI in early pregnancy and GWG rate in mid- and late-pregnancy were calculated. Childhood cardiometabolic traits were assessed at aged 4-7 years, including BMI, BMI-z, systolic blood pressure (SBP), diastolic blood pressure, high-density lipoprotein-cholesterol, low-density lipoprotein-cholesterol, total cholesterol, triglycerides, fasting glucose, and C-reactive protein. Each 1 kg/m2 increase in maternal BMI in early pregnancy was associated with 0.46% (95% confidence interval, 0.19%-0.72%) higher children BMI, 0.05 (0.02-0.08) higher BMI-z, 0.41% (0.22%-0.59%) higher waist circumference, and 0.24% (0.03%-0.46%) higher SBP. Each 1 kg/week higher GWG rate in mid- and late-pregnancy was associated with higher children SBP (4.58% [1.46%-7.71%]), triglycerides (18.28% [3.13%-33.44%]), and fasting glucose (5.83% [2.64%-9.02%]) and lower BMI-z (-0.45 [-0.82 to -0.08]). Additional adjustment for offspring BMI attenuated the associations for maternal BMI but not for GWG rate. CONCLUSIONS: The increase in maternal BMI and GWG are associated with adverse cardiometabolic profiles in childhood. The association between maternal BMI and childhood cardiometabolic traits is likely mediated using the offspring BMI.

Genome-wide identification and analysis of the WRKY gene family and low-temperature stress response in Prunus sibirica.

BACKGROUND: WRKY transcription factors are a prominent gene family in plants, playing a crucial role in various biological processes including development, metabolism, defense, differentiation, and stress response. Although the WRKY gene family has been extensively studied and analysed in numerous plant species, research on Prunus sibirica's WRKY genes (PsWRKY) remains lacking. RESULTS: This study analysed the basic physicochemical properties, phylogeny, gene structure, cis-acting elements, and Gene ontology (GO) annotation of PsWRKY gene family members using bioinformatics methods based on the whole-genome data of P. sibirica. In total, 55 WRKYs were identified in P. sibirica and were heterogeneously distributed on eight chromosomes. Based on the phylogenetic analysis, these WRKYs were classified into three major groups: Group I, Group II (II-a, II-b, II-c, II-d, II-e), and Group III. Members of different subfamilies have different cis-acting elements, conserved motifs, and intron-exon structures, indicating functional heterogeneity of the WRKY family. Prediction of subcellular localisation indicated that PsWRKYs were mainly located in the nucleus. Twenty pairs of duplicated genes were identified, and segmental duplication events may play an important role in PsWRKY gene family expansion. Analysis of the Ka/Ks ratio showed that the PsWRKY family's homologous genes were primarily purified by selection. Additionally, GO annotation analysis showed that the WRKY gene family was mainly involved in responses to stimuli, immune system processes, and reproductive processes. Furthermore, quantitative real-time PCR (qRT-PCR) analysis showed that 23 PsWRKYs were highly expressed in one or more tissues (pistils and roots) and PsWRKYs showed specific expression patterns under different low-temperature stress conditions. CONCLUSIONS: Our results provide a scientific basis for the further exploration and functional validation of WRKYs in P. sibirica.

Combined Morphological and Spectroscopic Diagnostic of HER2 Expression in Breast Cancer Tissues Based on Label-Free Surface-Enhanced Raman Scattering.

Breast cancer is the most commonly diagnosed cancer type worldwide. Overexpression of human epidermal growth factor receptor 2 (HER2) is an important subtype of breast cancer and results in an increased risk of recurrence and metastasis in patients. At present, immunohistochemistry (IHC) is used to detect the expression of HER2 in breast cancer tissues as the golden standard. However, IHC has some shortcomings, such as large subjective impact, long time consumption, expensive reagents, etc. In this paper, a combined morphological and spectroscopic diagnostic method based on label-free surface-enhanced Raman scattering (SERS) for HER2 expression in breast cancer is proposed. It can not only quantitively detect HER2 expression in breast cancer tissues by spectroscopic measurements but also give morphological images reflecting the distribution of HER2 in tissues. The results show that the consistency between this method and IHC is 95% and achieves the annotation of tumor regions on tissue sections. This method is time-consuming, quantifiable, intuitive, scalable, and easy to understand. Combined with deep learning approaches, it is expected to promote the development of clinical detection and diagnosis technology for breast cancer and other cancers.

On-Site Detection of SARS-CoV-2 Antigen by Deep Learning-Based Surface-Enhanced Raman Spectroscopy and Its Biochemical Foundations.

A rapid, on-site, and accurate SARS-CoV-2 detection method is crucial for the prevention and control of the COVID-19 epidemic. However, such an ideal screening technology has not yet been developed for the diagnosis of SARS-CoV-2. Here, we have developed a deep learning-based surface-enhanced Raman spectroscopy technique for the sensitive, rapid, and on-site detection of the SARS-CoV-2 antigen in the throat swabs or sputum from 30 confirmed COVID-19 patients. A Raman database based on the spike protein of SARS-CoV-2 was established from experiments and theoretical calculations. The corresponding biochemical foundation for this method is also discussed. The deep learning model could predict the SARS-CoV-2 antigen with an identification accuracy of 87.7%. These results suggested that this method has great potential for the diagnosis, monitoring, and control of SARS-CoV-2 worldwide.

High-throughput extracellular pH monitoring and antibiotics screening by polymeric fluorescent sensor with LCST property.

Monitoring extracellular pH (pHe) is important for biology understanding, since pHe and its homeostasis are closely relevant to cellular metabolism. Hydrogel-based pHe sensors have attracted significant attention and showed wide application, while they are tedious with significant time-cost operation and reproducibility variations for high-throughput application. Herein, we synthesized two polymers for pHe monitoring which are soluble in water at room temperature with easy operations and high reproducibility among various micro-plate wells for high-throughput analysis. P1 (P(OEGMA-co-MEO2MA-co-pHS)) and P2 (P(OEGMA-co-pHS)) were synthesized via the Reversible Addition Fragmentation Chain Transfer (RAFT) copolymerization of oligo(ethylene glycol) methacrylate (OEGMA), 2-(2'-methoxyethoxy) ethyl methacrylate (MEO2MA) and the pH sensitive fluorescence moiety N-fluoresceinyl methacrylamide (pHS). P1 is soluble in water at room temperature (25 °C) while insoluble at the temperature above 33 °C, indicating its feature of lower critical solution temperature (LCST) at 33 °C. Further P1 showed higher pH sensitivity and photostability than P2 (without LCST property) when used at physiological temperature (37 °C). Thus, P1 was chosen to in-situ monitor the micro-environmental acidification of E. coli, Hela and Ramos cells during their growth, and the metabolism inhibiting activity of a representative antibiotic, ampicillin. Cell concentration-dependent cellular acidification and drug concentration-dependent inhibition of cellular acidification were observed, demonstrating that the LCST polymer (P1) is suitable for real-time cellular acidification monitoring as well as for high-throughput drug screening. This study firstly demonstrated the use of a LCST polymeric sensor for high-throughput screening of antibiotics and investigation of cell metabolism.

Amphiphilic Fluorine-Containing Block Copolymers as Carriers for Hydrophobic PtTFPP for Dissolved Oxygen Sensing, Cell Respiration Monitoring and In Vivo Hypoxia Imaging with High Quantum Efficiency and Long Lifetime.

New amphiphilic star or multi-arm block copolymers with different structures were synthesized for enabling the use of hydrophobic oxygen probe of platinum (II)-tetrakis (pentafluorophenyl) porphyrin (PtTFPP) for bioanalysis. The amphiphilic star polymers were prepared through the Atom Transfer Radical Polymerization (ATRP) method by using hydrophilic 4-arm polyethylene glycol (4-arm-PEG) as an initiator. Among the five block copolymers, P1 series (P1a, P1b, and P1c) and P3 possess fluorine-containing moieties to improve the oxygen sensitivity with its excellent capacity to dissolve and carry oxygen. A polymer P2 without fluorine units was also synthesized for comparison. The structure-property relationship was investigated. Under nitrogen atmosphere, high quantum efficiency of PtTFPP in fluorine-containing micelles could reach to 22% and long lifetime could reach to 76 µs. One kind of representative PtTFPP-containing micelles was used to detect the respiration of Escherichia coli (E. coli) JM109 and macrophage cell J774A.1 by a high throughput plate reader. In vivo hypoxic imaging of tumor-bearing mice was also achieved successfully. This study demonstrated that using well-designed fluoropolymers to load PtTFPP could achieve high oxygen sensing properties, and long lifetime, showing the great capability for further in vivo sensing and imaging.

Targeting cardiac resident CCR2+ macrophage-secreted MCP-1 to attenuate inflammation after myocardial infarction.

After myocardial infarction (MI), cardiac resident CCR2+ macrophages release various cytokines and chemokines, notably monocyte chemoattractant protein-1 (MCP-1). MCP-1 is instrumental in recruiting CCR2+ monocytes to the damaged region. The excessive arrival of these monocytes, which then become macrophages, perpetuates inflammation at the site of injury. This continuous inflammation leads to adverse tissue remodeling and compromises cardiac function over time. We hypothesized that neutralizing the MCP-1 secreted by cardiac resident CCR2+ macrophages can mitigate post-MI inflammation by curtailing the recruitment of monocytes and their differentiation into macrophages. In this work, we developed nanoparticles that target the infarcted heart, specifically accumulating in the damaged area after intravenous (IV) administration, and docking onto CCR2+ macrophages. These nanoparticles were designed to slowly release an MCP-1 binding peptide, HSWRHFHTLGGG (HSW), which neutralizes the upregulated MCP-1. We showed that the HSW reduced monocyte migration, inhibited pro-inflammatory cytokine upregulation, and suppressed myofibroblast differentiation in vitro. After IV delivery, the released HSW significantly decreased monocyte recruitment and pro-inflammatory macrophage density, increased cardiac cell survival, attenuated cardiac fibrosis, and improved cardiac function. Taken together, our findings support the strategy of MCP-1 neutralization at the acute phase of MI as a promising way to alleviate post-MI inflammation. STATEMENT OF SIGNIFICANCE: After a myocardial infarction (MI), CCR2+ macrophages resident in the heart release various cytokines and chemokines, notably monocyte chemoattractant protein-1 (MCP-1). MCP-1 is instrumental in attracting CCR2+ monocytes to the damaged region. The excessive arrival of these monocytes, which then become macrophages, perpetuates inflammation at the site of injury. This continuous inflammation leads to adverse tissue remodeling and compromises cardiac function over time. In this work, we tested the hypothesis that neutralizing the MCP-1 secreted by cardiac CCR2+ macrophages can mitigate post-MI inflammation by curtailing the recruitment of monocytes.

The association of maternal gestational weight gain with cardiometabolic risk factors in offspring: a systematic review and meta-analysis.

CONTEXT: Gestational weight gain (GWG) is known to be a risk factor for offspring obesity, a precursor of cardiometabolic diseases. Accumulating studies have investigated the association of GWG with offspring cardiometabolic risk factors (CRFs), leading to inconsistent results. OBJECTIVE: This study synthesized available data from cohort studies to examine the effects of GWG on offspring CRFs. DATA SOURCE: Four electronic databases, including PubMed, Web of Science, Scopus, and Embase, were searched through May 2023. DATA EXTRACTION: Cohort studies evaluating the association between GWG and CRFs (fat mass [FM], body fat percentage [BF%], waist circumference [WC], systolic blood pressure [SBP] and diastolic blood pressure, high-density-lipoprotein cholesterol [HDL-C] and low-density-lipoprotein cholesterol, triglyceride [TG], total cholesterol, fasting blood glucose, and fasting insulin levels) were included. Regression coefficients, means or mean differences with 95% confidence intervals [CIs], or standard deviations were extracted. DATA ANALYSIS: Thirty-three cohort studies were included in the meta-analysis. Higher GWG (per increase of 1 kg) was associated with greater offspring FM (0.041 kg; 95% CI, 0.016 to 0.067), BF% (0.145%; 95% CI, 0.116 to 0.174), WC (0.154 cm; 95% CI, 0.036 to 0.272), SBP (0.040 mmHg; 95% CI, 0.010 to 0.070), and TG (0.004 mmol/L; 95% CI, 0.001 to 0.007), and with lower HDL-C (-0.002 mmol/L; 95% CI, -0.004 to 0.000). Consistently, excessive GWG was associated with higher offspring FM, BF%, WC, and insulin, and inadequate GWG was associated with lower BF%, low-density lipoprotein cholesterol, total cholesterol, and TG, compared with adequate GWG. Most associations went non-significant or attenuated with adjustment for offspring body mass index or FM. CONCLUSIONS: Higher maternal GWG is associated with increased offspring adiposity, SBP, TG, and insulin and decreased HDL-C in offspring, warranting a need to control GWG and to screen for cardiometabolic abnormalities of offspring born to mothers with excessive GWG. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration no. CRD42023412098.

An electron density clustering based adaptive segmentation method for protein Raman spectrum calculation.

Raman spectroscopy is a powerful technique for protein detection, but the calculation of Raman spectrum is a longstanding challenging problem due to the large sizes and complex structures of protein molecules. Dividing proteins into fragments can greatly accelerate the calculation, but this usually introduces large errors originating from ignored interactions between fragments into obtained spectra. In this paper, we proposed a new adaptive segmentation method based on the strength of interactions and molecular shapes and structures, i.e., electron density clustering, to divide proteins. It can reduce errors of obtained Raman spectra by about 20% compared to the uniform segmentation method without a significant increase in computational cost. This method can facilitate the validation and analysis of detected Raman spectra of proteins and promote the application of Raman spectroscopy in biological detection.

An in-situ method for SERS substrate preparation and optimization based on galvanic replacement reaction.

BACKGROUND: Various surface-enhanced Raman spectroscopy (SERS) substrate preparation methods have been reported, however, how to tune the "gap" between nanostructures to make more "hot spots" is still a barrier that restricts their application. The gap between nanostructures is usually fixed when the substrates are prepared. In other words, it is hard to tune interparticle distances for maximum electromagnetic coupling during substrate preparation process. Therefore, an in-situ substrate optimization method that could monitor the SERS signal intensity changes, i.e., to find the optimum gap width and particle size, during substrate preparation process is needed. RESULTS: A method based on the galvanic replacement reaction (GRR) is proposed for the in-situ gap width tuning between nanostructures as well as for the optimization of SERS substrates. Noble metal nanoparticles (NPs) form and grow on the sacrificial templates' surface while noble metal ions are reduced by sacrificial metal (oxides) in GRR. Along with the fresh and clean NPs' surface generated, the gap between two noble metal NPs decreases with the growth of the NPs. To demonstrate this strategy, cuprous oxide/Ti (Cu2O/Ti) sacrificial templates were prepared, and then a GRR was carried out with HAuCl4. The real-time SERS detection during GRR show that the optimum reaction time (ORT) is 300 ± 30 s. Furthermore, SERS performance testing was conducted on the optimized substrate, revealing that the detection limit for crystal violet can reach 1.96 × 10-11 M, confirming the feasibility of this method. SIGNIFICANCE AND NOVELTY: By monitoring the in-situ SERS signal of probes during GRR will obtain an "optimal state" of the SERS substrate with optimal gap width and particle size. The SERS substrate preparation and optimization strategy proposed in this article not only provides a simple, efficient, and low-cost method to fabricate surface-clean noble NPs but also paves the way for the in-situ optimization of NPs size and gap width between NPs which could achieve wider applications of SERS.

Genome-wide identification, expression analysis, and potential roles under low-temperature stress of bHLH gene family in Prunus sibirica.

The basic helix-loop-helix (bHLH) family is one of the most well-known transcription factor families in plants, and it regulates growth, development, and abiotic stress responses. However, systematic analyses of the bHLH gene family in Prunus sibirica have not been reported to date. In this study, 104 PsbHLHs were identified and classified into 23 subfamilies that were unevenly distributed on eight chromosomes. Nineteen pairs of segmental replication genes and ten pairs of tandem replication genes were identified, and all duplicated gene pairs were under purifying selection. PsbHLHs of the same subfamily usually share similar motif compositions and exon-intron structures. PsbHLHs contain multiple stress-responsive elements. PsbHLHs exhibit functional diversity by interacting and coordinating with other members. Twenty PsbHLHs showed varying degrees of expression. Eleven genes up-regulated and nine genes down-regulated in -4°C. The majority of PsbHLHs were highly expressed in the roots and pistils. Transient transfection experiments demonstrated that transgenic plants with overexpressed PsbHLH42 have better cold tolerance. In conclusion, the results of this study have significant implications for future research on the involvement of bHLH genes in the development and stress responses of Prunus sibirica.

Classification of Coronavirus Spike Proteins by Deep-Learning-Based Raman Spectroscopy and its Interpretative Analysis.

The outbreak of COVID-19 has spread worldwide, causing great damage to the global economy. Raman spectroscopy is expected to become a rapid and accurate method for the detection of coronavirus. A classification method of coronavirus spike proteins by Raman spectroscopy based on deep learning was implemented. A Raman spectra dataset of the spike proteins of five coronaviruses (including MERS-CoV, SARS-CoV, SARS-CoV-2, HCoVHKU1, and HCoV-OC43) was generated to establish the neural network model for classification. Even for rapidly acquired spectra with a low signal-to-noise ratio, the average accuracy exceeded 97%. An interpretive analysis of the classification results of the neural network was performed, which indicated that the differences in spectral characteristics captured by the neural network were consistent with the experimental analysis. The interpretative analysis method provided a valuable reference for identifying complex Raman spectra using deep-learning techniques. Our approach exhibited the potential to be applied in clinical practice to identify COVID-19 and other coronaviruses, and it can also be applied to other identification problems such as the identification of viruses or chemical agents, as well as in industrial areas such as oil and gas exploration.

Mining for genes related to pistil abortion in Prunus sibirica L.

In Prunus sibirica, the phenomenon of pistil abortion is very common and seriously affects its fruit quality and yield; however, the molecular mechanisms of pistil abortion remains unclear. In this study, we identified differentially expressed genes (DEGs) and pathways associated with pistil abortion using transcriptome sequencing. After comparative analysis, a total of 1,950 DEGs were identified, of which 1,000 were upregulated, and 950 were downregulated. Gene Ontology (GO) functional enrichment analysis of DEGs showed that metabolic process, cellular process, single-organism process, membrane, membrane part, cell, binding, catalytic activity, and transporter activity contained the largest number of DEGs. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that the plant-pathogen interaction, starch and sucrose metabolism, and plant hormone signal transduction pathways contained the largest number of DEGs. The NAC, bHLH, and B3 transcription factor families contained the largest number of DEGs. qRT-PCR detection confirmed that the gene expression levels were consistent with the transcriptome sequencing results. This study provides a theoretical basis and scientific basis for further research on the molecular mechanisms of P. sibirica pistil abortion.

Rescuing Cardiac Cells and Improving Cardiac Function by Targeted Delivery of Oxygen-Releasing Nanoparticles after or Even before Acute Myocardial Infarction.

Myocardial infarction (MI) causes massive cell death due to restricted blood flow and oxygen deficiency. Rapid and sustained oxygen delivery following MI rescues cardiac cells and restores cardiac function. However, current oxygen-generating materials cannot be administered during acute MI stage without direct injection or suturing methods, both of which risk rupturing weakened heart tissue. Here, we present infarcted heart-targeting, oxygen-releasing nanoparticles capable of being delivered by intravenous injection at acute MI stage, and specifically accumulating in the infarcted heart. The nanoparticles can also be delivered before MI, then gather at the injured area after MI. We demonstrate that the nanoparticles, delivered either pre-MI or post-MI, enhance cardiac cell survival, stimulate angiogenesis, and suppress fibrosis without inducing substantial inflammation and reactive oxygen species overproduction. Our findings demonstrate that oxygen-delivering nanoparticles can provide a nonpharmacological solution to rescue the infarcted heart during acute MI and preserve heart function.

Prevalence and related factors of child posttraumatic stress disorder during COVID-19 pandemic: A systematic review and meta-analysis.

BACKGROUND: The COVID-19 pandemic has drastically impacted many aspects of society and has indirectly produced various psychological consequences. This systematic review aimed to estimate the worldwide prevalence of posttraumatic stress disorder (PTSD) in children due to the COVID-19 pandemic, as well as to identify protective or risk factors contributing to child PTSD. METHODS: We conducted a systematic literature search in the PubMed, ProQuest, PsycINFO, Embase, Web of Science, WanFang, CNKI, and VIP databases. We searched for studies published between January 1, 2020 and May 26, 2021, that reported the prevalence of child PTSD due to the COVID-19 pandemic, as well as factors contributing to child PTSD. Eighteen studies were included in our systematic review, of which 10 studies were included in the meta-analysis. RESULTS: The estimated prevalence of child PTSD after the COVID-19 outbreak was 28.15% (95% CI: 19.46-36.84%, I2 = 99.7%). In subgroup analyses for specific regions the estimated prevalence of post-pandemic child PTSD was 19.61% (95% CI: 11.23-27.98%) in China, 50.8% (95% CI: 34.12-67.49%) in the USA, and 50.08% in Italy (95% CI: 47.32-52.84%). CONCLUSIONS: Factors contributing to child PTSD were categorized into four aspects: personal factors, family factors, social factors and infectious diseases related factors. Based on this, we presented a new framework summarizing the occurrence and influence of the COVID-19 related child PTSD, which may contribute to a better understanding, prevention and development of interventions for child PTSD in forthcoming pandemics.

Flexible SnTe/carbon nanofiber membrane as a free-standing anode for high-performance lithium-ion and sodium-ion batteries.

Flexible electrode plays a key role in flexible energy storage devices. The SnTe/C nanofibers membrane (SnTe/CNFM) with excellent mechanical flexibility has been successfully synthesized for the first time through electrospinning, and it demonstrates outstanding electrochemical performance as free-standing anode for lithium/sodium-ion batteries. The SnTe/CNFM electrode delivers a discharge capacity of 526.7 mAh g-1 at 1000 mA g-1 after 1000 cycles in lithium-ion half-cells and a discharge capacity of 236.5 mAh g-1 at 500 mA g-1 after 80 cycles in lithium-ion full-cells with a LiFePO4 cathode. Not only that, it shows a discharge capacity of 182.7 mAh g-1 at 200 mA g-1 after 200 cycles in sodium-ion half-cells and a high discharge capacity of 207.0 mAh g-1 at 500 mA g-1 after 50 cycles in sodium-ion full-cells with a Na0.44MnO2 cathode. Moreover, the prepared SnTe/CNFM exhibits good mechanical flexibility. The SnTe/CNFM can still return to its original state without any breakage after bending, curling, folding and kneading. These results indicate that SnTe/CNFM is expected to become one of the promising free-standing anodes for lithium/sodium-ion batteries.

Wire-in-Wire TiO2/C Nanofibers Free-Standing Anodes for Li-Ion and K-Ion Batteries with Long Cycling Stability and High Capacity.

Wearable and portable mobile phones play a critical role in the market, and one of the key technologies is the flexible electrode with high specific capacity and excellent mechanical flexibility. Herein, a wire-in-wire TiO2/C nanofibers (TiO2 ww/CN) film is synthesized via electrospinning with selenium as a structural inducer. The interconnected carbon network and unique wire-in-wire nanostructure cannot only improve electronic conductivity and induce effective charge transports, but also bring a superior mechanic flexibility. Ultimately, TiO2 ww/CN film shows outstanding electrochemical performance as free-standing electrodes in Li/K ion batteries. It shows a discharge capacity as high as 303 mAh g-1 at 5 A g-1 after 6000 cycles in Li half-cells, and the unique structure is well-reserved after long-term cycling. Moreover, even TiO2 has a large diffusion barrier of K+, TiO2 ww/CN film demonstrates excellent performance (259 mAh g-1 at 0.05 A g-1 after 1000 cycles) in K half-cells owing to extraordinary pseudocapacitive contribution. The Li/K full cells consisted of TiO2 ww/CN film anode and LiFePO4/Perylene-3,4,9,10-tetracarboxylic dianhydride cathode possess outstanding cycling stability and demonstrate practical application from lighting at least 19 LEDs. It is, therefore, expected that this material will find broad applications in portable and wearable Li/K-ion batteries.

Red phosphorus embedded in TiO2/C nanofibers to enhance the potassium-ion storage performance.

TiO2-red phosphorus/C nanofibers (TiO2-RP/CN) have been synthesized via electrospinning and then annealed with red phosphorus sublimation. Benefiting from the high electronic/ionic conductivity and robust stability of the unique structure, the TiO2-RP/CN show high reversible capacities, as well as an outstanding cycling ability. In K half cells, the capacity decay of the TiO2-RP/CN electrode mainly occurs in the first few cycles, and at 0.05 A g-1 it delivers a high specific capacity of 257.8 mA h g-1 after 500 cycles. K full cells were fabricated; these are well-matched with PTCDA (perylene-3,4,9,10-tetracarboxylic dianhydride) and also exhibited a good electrochemical performance (62 mA h g-1 after 100 cycles). Therefore, the TiO2-RP/CN are potential anode materials for use in K-ion batteries.